“Harmonic 3D shape matching” by Kazhdan and Funkhouser

  • ©Michael Kazhdan and Thomas (Tom) A. Funkhouser

Conference:


Type:


Interest Area:


    Application

Title:

    Harmonic 3D shape matching

Session/Category Title:   Shape


Presenter(s)/Author(s):



Abstract:


    With the advent of the world wide web, the number of available 3D models has increased substantially and the challenge has changed from “How do we generate 3D models?” to “How do we find them?” In this sketch we describe a new 3D model matching and indexing algorithm that uses spherical harmonics to compute discriminating similarity measures without requiring repair of model degeneracies or alignment of orientations. It provides 46-245% better performance than related shape matching methods during precision-recall experiments, and it is fast enough to return query results from a repository of 20,000 models in under half a second.

References:


    1. Ankerst, M., Kastenmüller, G., Kriegel, H.-P., and Seidl, T. 1999. 3d shape histograms for similarity search and classification in spatial databases. In Proc. SSD, 207–226.
    2. Elad, M., Tal, A., and Ar, S. 2001. Content based retrieval of vrml objects – an iterative and interactive approach. EG Multimedia (September), 97–108.
    3. Horn, B. 1984. Extended gaussian images. Proc. of the IEEE 72, 12 (December), 1671–1686.
    4. Osada, R., Funkhouser, T., Chazelle, B., and Dobkin, D. 2001. Matching 3d models with shape distributions. Shape Modeling International (May).


ACM Digital Library Publication:



Overview Page: